Abstract: The evolutionary origins of most pathogenic microbes are rooted in free-living, benign ancestral organisms that, through acquisition and innovation, gain new gene functions and, with them, the ability to colonize new habitats (e.g., a human host). The specific roles of these new genes are often known, whether it be antigenic variability or cell invasion, but the properties of the genetic sequences that enable such functions are poorly understood. Many of the questions that remain unanswered can be investigated with an evolutionary approach that can provide perspective on (i) where do the pathogenicity-related genes come from, (ii) how and if can we identify signatures of pathogenicity within sequences, and (iii) the possibility of predicting the emergence of pathogenicity based on gene evolution. These questions can be answered with computational approaches to investigate genome complexity within the genus Plasmodium, which is the agent of malaria. Plasmodia are known for their high frequency of low complexity regions (LCRs) that are segments of genome with lower-than-expected nucleotide and amino acid diversity. LCRs are also known for their high rate of changes, which makes them excellent candidates for sources of genetic innovations and new functions. The first aim of the proposed project consists in the development of new computational measures to identify sequences involved in genome complexity. The second aim is a comparative analysis of protein coding genes with and without LCRs to determine the primary forces driving their evolution. The reconstruction of ancestral states in these genes will allow to identify evolutionary mechanisms and selective pressures at the origin of LCRs and their potential connection to the evolution of pathogenic lifestyles. The third aim will be a functional analysis of genes with and without LCRs to determine computationally if these regions are essential for the proper formation of a functioning product. Compositional biases, length variation, and evolutionary histories across species will be used to determine conservation of these regions through time and correlate this information with gene function. The proposed research will provide new insights into the evolution of pathogenesis and its signatures within genomes of the genus Plasmodium.